Dongming Zhou

4.5k total citations · 1 hit paper
178 papers, 3.4k citations indexed

About

Dongming Zhou is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Electrical and Electronic Engineering. According to data from OpenAlex, Dongming Zhou has authored 178 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Computer Vision and Pattern Recognition, 72 papers in Media Technology and 24 papers in Electrical and Electronic Engineering. Recurrent topics in Dongming Zhou's work include Advanced Image Fusion Techniques (67 papers), Image Enhancement Techniques (45 papers) and Remote-Sensing Image Classification (28 papers). Dongming Zhou is often cited by papers focused on Advanced Image Fusion Techniques (67 papers), Image Enhancement Techniques (45 papers) and Remote-Sensing Image Classification (28 papers). Dongming Zhou collaborates with scholars based in China, South Korea and United States. Dongming Zhou's co-authors include Jinde Cao, Rencan Nie, Yanbu Guo, Kangjian He, Xin Jin, Ruichao Hou, Zhengqiu Zhang, Shaowen Yao, Qian Jiang and Xiaoli Ruan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Expert Systems with Applications and IEEE Access.

In The Last Decade

Dongming Zhou

171 papers receiving 3.3k citations

Hit Papers

LightingNet: An Integrated Learning Method for Low-Light ... 2023 2026 2024 2025 2023 25 50 75 100

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dongming Zhou China 30 1.5k 1.5k 645 538 430 178 3.4k
Bin Yu China 18 426 0.3× 704 0.5× 731 1.1× 416 0.8× 122 0.3× 87 2.6k
Ehsan Elhamifar United States 20 1.1k 0.7× 3.2k 2.2× 98 0.2× 1.7k 3.2× 127 0.3× 50 4.4k
Qingbo Wu China 30 839 0.5× 2.6k 1.8× 415 0.6× 667 1.2× 144 0.3× 223 3.5k
Shuang Xu China 27 959 0.6× 1.4k 0.9× 59 0.1× 575 1.1× 204 0.5× 149 2.7k
Bo Chen China 31 409 0.3× 1.6k 1.1× 167 0.3× 1.5k 2.7× 1.7k 3.9× 211 4.4k
Bijoy K. Ghosh United States 35 210 0.1× 681 0.5× 804 1.2× 493 0.9× 643 1.5× 212 4.0k
Kai Liu China 26 860 0.6× 1.4k 0.9× 90 0.1× 173 0.3× 236 0.5× 270 3.5k
Weiwei Wang China 20 333 0.2× 613 0.4× 301 0.5× 194 0.4× 135 0.3× 139 1.9k
Xu Liu China 31 875 0.6× 1.3k 0.9× 62 0.1× 659 1.2× 443 1.0× 224 3.0k
Thrasyvoulos N. Pappas United States 28 431 0.3× 2.0k 1.4× 420 0.7× 279 0.5× 69 0.2× 154 3.2k

Countries citing papers authored by Dongming Zhou

Since Specialization
Citations

This map shows the geographic impact of Dongming Zhou's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dongming Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dongming Zhou more than expected).

Fields of papers citing papers by Dongming Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dongming Zhou. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dongming Zhou. The network helps show where Dongming Zhou may publish in the future.

Co-authorship network of co-authors of Dongming Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Dongming Zhou. A scholar is included among the top collaborators of Dongming Zhou based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dongming Zhou. Dongming Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Fangfang, et al.. (2025). MKFTracker: An RGBT tracker via multimodal knowledge embedding and feature interaction. Knowledge-Based Systems. 310. 112860–112860.
2.
Liu, Yanyu, et al.. (2025). ACL-Net: Attribute-Aware Contrastive Learning Network for Medical Image Fusion. IEEE Signal Processing Letters. 32. 2484–2488. 1 indexed citations
3.
Bao, Liyong, et al.. (2025). Construction and Attractor Analysis of Discrete Chaotic Systems Based on Julia Fractal Transformation. International Journal of Bifurcation and Chaos. 35(2).
4.
Hou, Ruichao, Xingyuan Li, Tongwei Ren, et al.. (2025). HyPSAM: Hybrid Prompt-Driven Segment Anything Model for RGB-Thermal Salient Object Detection. IEEE Transactions on Circuits and Systems for Video Technology. 36(3). 2697–2712.
6.
Li, Hui, Ting Wu, Xin Qi, et al.. (2024). Microscopic identification of foodborne bacterial pathogens based on deep learning method. Food Control. 161. 110413–110413. 12 indexed citations
7.
Zhou, Dongming, et al.. (2024). Focus-aware and deep restoration network with transformer for multi-focus image fusion. Digital Signal Processing. 149. 104473–104473. 3 indexed citations
8.
Zhou, Dongming, et al.. (2023). Dynamic hypergraph convolutional network for multimodal sentiment analysis. Neurocomputing. 565. 126992–126992. 19 indexed citations
9.
Shi, Hang, et al.. (2023). Co-space Representation Interaction Network for multimodal sentiment analysis. Knowledge-Based Systems. 283. 111149–111149. 15 indexed citations
10.
Zhou, Dongming, et al.. (2023). Robust multi-focus image fusion using focus property detection and deep image matting. Expert Systems with Applications. 237. 121389–121389. 5 indexed citations
11.
Guo, Yanbu, Dongming Zhou, Xiaoli Ruan, & Jinde Cao. (2023). Variational gated autoencoder-based feature extraction model for inferring disease-miRNA associations based on multiview features. Neural Networks. 165. 491–505. 91 indexed citations
12.
Liu, Yanyu, et al.. (2023). An Improved Hybrid Network With a Transformer Module for Medical Image Fusion. IEEE Journal of Biomedical and Health Informatics. 27(7). 3489–3500. 23 indexed citations
13.
Liu, Yanyu, et al.. (2022). TSE_Fuse: Two stage enhancement method using attention mechanism and feature-linking model for infrared and visible image fusion. Digital Signal Processing. 123. 103387–103387. 12 indexed citations
14.
Zhou, Dongming, et al.. (2022). EDAfuse: A encoder–decoder with atrous spatial pyramid network for infrared and visible image fusion. IET Image Processing. 17(1). 132–143. 4 indexed citations
15.
Liu, Yanyu, et al.. (2022). Asymmetric Global–Local Mutual Integration Network for RGBT Tracking. IEEE Transactions on Instrumentation and Measurement. 71. 1–17. 22 indexed citations
16.
Liu, Yanyu, Ruichao Hou, Dongming Zhou, et al.. (2020). Multimodal medical image fusion based on the spectral total variation and local structural patch measurement. International Journal of Imaging Systems and Technology. 31(1). 391–411. 11 indexed citations
17.
Zhang, Ziyi, et al.. (2013). Sensitivity study for improved magnetic induction tomography (MIT) coil system. International Symposium on Antennas and Propagation. 2. 1317–1320. 4 indexed citations
18.
Zhou, Dongming, et al.. (2009). Color image segmentation and edge detection using Unit-Linking PCNN and image entropy. Computer Engineering and Applications Journal. 45(12). 2 indexed citations
19.
Zhou, Dongming. (2002). Globally Exponential Stability of Cellular Neural Networks with Time-varying Delays. Yunnan Daxue xuebao. Shehui kexue ban. 1 indexed citations
20.
Zhou, Dongming, et al.. (1998). STABILITY ANALYSIS ON DELAYED CELLULAR NEURAL NETWORKS. Information and Computation. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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